Nadine Salzmann

Recent and future warm extreme events and high-mountain slope stability

The number of large slope failures in some high-mountain regions such as the European Alps has increased during the past two to three decades. There is concern that recent climate change is driving this increase in slope failures, thus possibly further exacerbating the hazard in the future. Although the effects of a gradual temperature rise on glaciers and permafrost have been extensively studied, the impacts of short-term, unusually warm temperature increases on slope stability in high mountains remain largely unexplored. We describe several large slope failures in rock and ice in recent years in Alaska, New Zealand and the European Alps, and analyse weather patterns in the days and weeks before the failures. Although we did not find one general temperature pattern, all the failures were preceded by unusually warm periods; some happened immediately after temperatures suddenly dropped to freezing. We assessed the frequency of warm extremes in the future by analysing eight regional climate models from the recently completed European Union programme ENSEMBLES for the central Swiss Alps. The models show an increase in the higher frequency of high-temperature events for the period 2001–2050 compared with a 1951–2000 reference period. Warm events lasting 5, 10 and 30 days are projected to increase by about 1.5–4 times by 2050 and in some models by up to 10 times. Warm extremes can trigger large landslides in temperature-sensitive high mountains by enhancing the production of water by melt of snow and ice, and by rapid thaw. Although these processes reduce slope strength, they must be considered within the local geological, glaciological and topographic context of a slope.

Assessment of the hazard potential of ice avalanches using remote sensing and GIS‐modelling

Ice avalanches typically occur when a large mass of ice breaks off from steep glaciers. Since the reach of ice avalanches is usually low, their hazard potential is generally restricted to high mountain areas that are densely populated or frequently visited by tourists. However, far‐reaching disasters are possible in combination with other processes such as rockfalls or snow avalanches. In addition, the hazard potential of ice avalanches is presently increasing as a consequence of climatic and socio‐economic changes in mountain areas. Dealing with ice‐avalanche hazards requires robust tools for systematic area‐wide detection of hazard potentials. Corresponding techniques have not been developed so far. To bridge this methodological gap, a three‐level downscaling approach was developed. This method chain is based on statistical parameters, geographic information system (GIS) modelling techniques and remote sensing. The procedure permits to perform a fast and systematic first‐order mapping of potentially dangerous steep glaciers and their runout paths for an entire region. To validate the approach, a case study was carried out in the Bernese Alps, Switzerland. The results correspond well with local studies using dynamic avalanche models. Improvements can be obtained by expanding the method chain by including basic data of higher spatial resolution as satellite data and digital terrain models (DTM).

GIS‐based modeling of glacial hazards and their interactions using Landsat‐TM and IKONOS imagery

Hazard interactions in glacial and periglacial environments are of crucial importance due to their potential for causing major catastrophes. Nevertheless, glacial and periglacial hazards have usually been modeled separately to date. In this study, we therefore propose a methodological strategy for modeling and assessing glacial and periglacial hazard interactions on a regional scale, including ice avalanches, lake outbursts and periglacial debris flows. Due to climate‐related rapid changes in glacial and periglacial areas, methods which incorporate monitoring capacities are needed. Hence, the methods presented here are based on remote sensing data, which are particularly powerful for monitoring tasks, and GIS modeling. For ice avalanche and lake‐outburst hazard detection and modeling, we applied recently published methods based on Landsat‐TM imagery, terrain modeling and flow routing. For detection of potential debris‐flow initiation zones in steep debris reservoirs, we present a novel method based on image processing of IKONOS data and terrain modeling, followed by flow modeling. Using this method, we achieve the synthesis of the individual process modeling in order to assess the potential interactions. The modeling is applied to a study region in the central Swiss Alps. The results show that systematic modeling based on remote sensing and GIS is suitable for first‐order assessment of glacial and periglacial hazard interactions as well as assessments of possible consequences, including impacts on traffic routes and other infrastructure. Based on this, critical cases can be detected and analyzed by subsequent detailed studies.

Assessing the Performance of Multiple Regional Climate Model Simulations for Seasonal Mountain Snow in the Upper Colorado River Basin

AbstractThis study assesses the performance of the regional climate model (RCM) simulations from the North American Regional Climate Change Assessment Program (NARCCAP) for the Upper Colorado River basin (UCRB), U.S. Rocky Mountains. The UCRB is a major contributor to the Colorado River’s runoff. Its significant snow-dominated hydrological regime makes it highly sensitive to climatic changes, and future water shortage in this region is likely. The RCMs are evaluated with a clear RCM output user’s perspective and a main focus on snow. Snow water equivalent (SWE) and snow duration, as well as air temperature and precipitation from five RCMs, are compared with snowpack telemetry (SNOTEL) observations, with National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) Reanalysis II (R2), which provides the boundary conditions for the RCM simulations, and with North American Regional Reanalysis (NARR). Overall, most RCMs were able to significantly improve on the results f...

Coupling terrestrial and atmospheric water dynamics to improve prediction in a changing environment

Humans have profoundly influenced their environment. It has been estimated that nearly one-third of the global land cover has been modified while approximately 40% of the photosynthesis has been appropriated. As the interface between the subsurface and the atmosphere is altered, it is imperative that we understand the influence this alteration has in terms of changing regional and global climates. Land surface heterogeneity is sometimes a principal modulator of local and regional climates and, as such, there are potential aggregation and teleconnection effects ranging in scales from soil pores to the general atmospheric circulation when the land surface is altered across a range of scales. The human fingerprint on land surface processes is critical and must also be accounted for in the discourse on land-atmosphere coupling as it pertains to climate and global change as well as local processes such as evapotranspiration and streamflow. It is at this pivotal interface where hydrologists, atmospheric scientists and ecologists must understand how their disciplines interact and influence each other.Fluxes across the land-surface directly influence predictions of ecological processes, atmospheric dynamics, and terrestrial hydrology. However, many simplifications are made in numerical models when considering terrestrial hydrology from the view point of the atmosphere and visa-versa. While this may be a necessity in the current generation of operational models used for forecasting, it can create obstacles to the advancement of process understanding. These simplifications can limit the numerical prediction capabilities on how water partitions itself throughout all phases of the water cycle. The feedbacks between terrestrial and atmospheric water dynamics are not well understood or represented by the current generation of operational land-surface and atmospheric models. This can lead to erroneous spatial patterns and anomalous temporal persistence in land-atmosphere exchanges and atmospheric water cycle predictions. Cross-disciplinary efforts are needed not only to identify but also to quantify feedbacks between terrestrial and atmospheric water at appropriate spatiotemporal scales. This is especially true as today’s young scientists set their sights on improving process understanding and prediction skill from both research and operational models used to describe such linked systems.In recognition of these challenges, a junior faculty and early career scientist forum was recently held at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado with the intent of identifying and characterizing feedback interactions, and their attendant spatial and temporal scales, important for coupling terrestrial and atmospheric water dynamics. The primary focus of this forum is on improved process understanding, rather than operational products, as the possibility of incorporating more realistic physics into operational models is computationally prohibitive. We approached the subject of improved predictability through better process understanding by focusing on the following three framework questions described and discussed below.

Facing unprecedented drying of the Central Andes? Precipitation variability over the period AD 1000–2100

Projected future trends in water availability are associated with large uncertainties in many regions of the globe. In mountain areas with complex topography, climate models have often limited capabilities to adequately simulate the precipitation variability on small spatial scales. Also, their validation is hampered by typically very low station density. In the Central Andes of South America, a semi-arid high-mountain region with strong seasonality, zonal wind in the upper troposphere is a good proxy for interannual precipitation variability. Here, we combine instrumental measurements, reanalysis and paleoclimate data, and a 57-member ensemble of CMIP5 model simulations to assess changes in Central Andes precipitation over the period AD 1000–2100. This new database allows us to put future projections of precipitation into a previously missing multi-centennial and pre-industrial context. Our results confirm the relationship between regional summer precipitation and 200 hPa zonal wind in the Central Andes, with stronger Westerly winds leading to decreased precipitation. The period of instrumental coverage (1965–2010) is slightly dryer compared to pre-industrial times as represented by control simulations, simulations from the past Millennium, ice core data from Quelccaya ice cap and a tree-ring based precipitation reconstruction. The model ensemble identifies a clear reduction in precipitation already in the early 21st century: the 10 year running mean model uncertainty range (ensemble 16–84% spread) is continuously above the pre-industrial mean after AD 2023 (AD 2028) until the end of the 21st century in the RCP2.6 (RCP8.5) emission scenario. Average precipitation over AD 2071–2100 is outside the range of natural pre-industrial variability in 47 of the 57 model simulations for both emission scenarios. The ensemble median fraction of dry years (defined by the 5th percentile in pre-industrial conditions) is projected to increase by a factor of 4 until 2071–2100 in the RCP8.5 scenario. Even under the strong reduction of greenhouse gas emissions projected by the RCP2.6 scenario, the Central Andes will experience a reduction in precipitation outside pre-industrial natural variability. This is of concern for the Central Andes, because society and economy are highly vulnerable to changes in the hydrological cycle and already have to face decreases in fresh water availability caused by glacier retreat.

Missing (in-situ) snow cover data hampers climate change and runoff studies in the Greater Himalayas.

The Himalayas are presently holding the largest ice masses outside the polar regions and thus (temporarily) store important freshwater resources. In contrast to the contemplation of glaciers, the role of runoff from snow cover has received comparably little attention in the past, although (i) its contribution is thought to be at least equally or even more important than that of ice melt in many Himalayan catchments and (ii) climate change is expected to have widespread and significant consequences on snowmelt runoff. Here, we show that change assessment of snowmelt runoff and its timing is not as straightforward as often postulated, mainly as larger partial pressure of H2O, CO2, CH4, and other greenhouse gases might increase net long-wave input for snowmelt quite significantly in a future atmosphere. In addition, changes in the short-wave energy balance - such as the pollution of the snow cover through black carbon - or the sensible or latent heat contribution to snowmelt are likely to alter future snowmelt and runoff characteristics as well. For the assessment of snow cover extent and depletion, but also for its monitoring over the extremely large areas of the Himalayas, remote sensing has been used in the past and is likely to become even more important in the future. However, for the calibration and validation of remotely-sensed data, and even more so in light of possible changes in snow-cover energy balance, we strongly call for more in-situ measurements across the Himalayas, in particular for daily data on new snow and snow cover water equivalent, or the respective energy balance components. Moreover, data should be made accessible to the scientific community, so that the latter can more accurately estimate climate change impacts on Himalayan snow cover and possible consequences thereof on runoff.

Permafrost model sensitivity to seasonal climatic changes and extreme events in mountainous regions

Climate models project considerable ranges and uncertainties in future climatic changes. To assess the potential impacts of climatic changes on mountain permafrost within these ranges of uncertainty, this study presents a sensitivity analysis using a permafrost process model combined with climate input based on delta-change approaches. Delta values comprise a multitude of coupled air temperature and precipitation changes to analyse long-term, seasonal and seasonal extreme changes on a typical low-ice content mountain permafrost location in the Swiss Alps. The results show that seasonal changes in autumn (SON) have the largest impact on the near-surface permafrost thermal regime in the model, and lowest impacts in winter (DJF). For most of the variability, snow cover duration and timing are the most important factors, whereas maximum snow height only plays a secondary role unless maximum snow heights are very small. At least for the low-ice content site of this study, extreme events have only short-term effects and have less impact on permafrost than long-term air temperature trends.

The Swiss Alpine glaciers' response to the global '2 C air temperature target'

While there is general consensus that observed global mean air temperature has increased during the past few decades and will very likely continue to rise in the coming decades, the assessment of the effective impacts of increased global mean air temperature on a specific regional-scale system remains highly challenging. This study takes up the widely discussed concept of limiting global mean temperature to a certain target value, like the so-called 2 °C target, to assess the related impacts on the Swiss Alpine glaciers. A model setup is introduced that uses and combines homogenized long-term meteorological observations and three ensembles of transient gridded Regional Climate Model simulations to drive a distributed glacier mass balance model under a (regionalized) global 2 °C target scenario. 101 glaciers are analyzed representing about 50% of the glacierized area and 75% of the ice volume in Switzerland. In our study, the warming over Switzerland, which corresponds to the global 2 °C target is met around 2030, 2045 and 2055 (depending on the ensemble) for Switzerland, and all glaciers have fully adjusted to the new climate conditions at around 2150. By this time and relative to the year 2000, the glacierized area and volume are both decreased to about 35% and 20%, respectively, and glacier-based runoff is reduced by about 70%.

Towards remote monitoring of sub-seasonal glacier mass balance

Abstract This study presents a method that allows continuous monitoring of mass balance for remote or inaccessible glaciers, based on repeated oblique photography. Hourly to daily pictures from two automatic cameras overlooking two large valley glaciers in the Swiss Alps are available for eight ablation seasons (2004–11) in total. We determine the fraction of snow-covered glacier surface from orthorectified and georeferenced images and combine this information with simple accumulation and melt modelling using meteorological data. By applying this approach, the evolution of glacier-wide mass balance throughout the ablation period can be directly calculated, based on terrestrial remote-sensing data. Validation against independent in situ mass-balance observations indicates good agreement. Our methodology has considerable potential for the remote determination of mountain glacier mass balance at high temporal resolution and could be applied using both repeated terrestrial and air-/spaceborne observations.